Videogames will revolutionize school (not necessarily the way you think)
A lot of the hype around educational games centers around “gamification”, and using game techniques to make the boring drilling of facts into something more fun. Which would be a definite improvement, but I don’t think that it’s ambitious enough.
Instead, let’s start by considering the question: what kind of things should education teach, and why?
Typically, school has taught facts. Bad school systems only focus on teaching facts and testing the extent to which they have been memorized, good school systems also make at least some effort to test the ability to apply them. Unfortunately, it is hard to test the ability to apply something, but easy to test whether it has been memorized. But the ability to memorize something says nothing about whether it was understood, so we get laments like the following:
For example, consider college freshmen who have taken their first college-level physics class, passed it with good grades, and can write down Newton’s laws of motion. […] Lots of studies have shown that many such students, students who can write down Newton’s laws of motion, if asked so simple a question as “How many forces are acting on a coin when it has been thrown up into the air?” (the answer to which can actually be deduced from Newton’s laws) get the answer wrong. Leaving aside friction, they claim that two forces are operating on the coin, gravity and “impetus,” the force the hand has transferred to the coin. Gravity exists as a force and, according to Newton’s laws, is the sole force acting on the coin when it is in the air (aside from air friction). Impetus, in the sense above, however, does not exist, though Aristotle thought it did and people in their everyday lives tend to view force and motion in such terms quite naturally.
So these students have entered the semiotic domain of physics as passive content but not as something in terms of which they can actually see and operate on their world in new ways. There may be nothing essentially wrong with this, since their knowledge of such passive content might help them know, at some level, what physics, an important enterprise in modern life, is “about.” I tend to doubt this, however. Be that as it may, these students cannot produce meanings in physics or understand them in producerlike ways.
They have not learned to experience the world in a new way. They have not learned to experience the world in a way in which the natural inclination to think in terms of the hand transmitting a force to the coin, a force that the coin stores up and uses up (“impetus”), is not part of one’s way of seeing and operating on the world (for a time and place, i.e., when doing modern physics). — James Paul Gee, What Video Games Have to Teach Us about Learning and Literacy, pp. 22-23
The issue that Gee is really highlighting is the fact that although students have learned some words, the mental model of physics that they have is one of folk physics, not scientific physics. A mental model, as I’m using the term, is a mental simulation of some set of laws of cause and effect that exist in the world. If you have a well-formed model of physics, you can ask yourself questions like “how would this object behave under the influence of these forces” or “what forces are acting on this object in this situation”, study your model, and get an answer back.
A mental model doesn’t need to be about a formal and easily-defined domain such as physics: most aren’t. Whenever you hear somebody make a claim that makes you think “that doesn’t sound quite right”, the claim has violated the predictions of your existing models. Models can be very extensive or very limited: a young child might know that on ordinary days of the week, mother will return from work at 5 PM, but have no other idea of what “work” means.
But the important thing about mental models is that they simulate parts of reality. And reality is a dynamic process, where things are constantly changing in ways that we wish to predict. Simulations of reality, in order to be useful, must then be processes as well.
For example, simply knowing that an object in free fall on Earth will accelerate at 9.81 m/s per second isn’t very useful if one only understands it as a string of English words. Physics students need to understand that it is actually a description of a dynamic process, a characterization of the way that a falling object behaves over time. They haven’t really learned the meaning of this before they can use the information to imagine and predict what happens if they drop a rock from their balcony. Although we want our students to learn dynamic models and to understand processes, for the most part we have been forced to communicate those models via static representations (writing, pictures) that require highly non-trivial mental effort to translate into dynamic models.
But we now have computer programs, which can actually function as dynamic representations. A computer program is a process by its very nature, and it can in principle made to represent almost arbitrary other processes. We’re no longer just forced to use a static representation of a dynamic process when we can instead give a student something dynamic to play with. This should hopefully make it much easier to turn the learned content into a dynamic mental model from the start.
This also suggests that we should reconsider the very things that we are teaching in school – today’s curriculum has been shaped by what’s possible or easy to teach and test using only static representations, but computer programs allow for much more dynamic teaching and testing. Instead of telling a student, “you’ll pass if you can write an essay that lists the reasons why the Roman Empire fell”, a teacher could instead say, “you’ll pass if you play this computer game where you’re the ruler of Rome and succeed in preventing its fall”. The essay basically only tests memorization, while the game – if it has been well-designed – tests the ability to actually apply the knowledge, to correctly identify the reasons for the empire’s fall and to then counteract them.
But the reasons for the fall of the Roman Empire, too, are something that’s taken from the current curriculum, which we might want to reconsider entirely. What kinds of models do we want to teach our children, and why? Perhaps what we’re really after is a more general notion of why different societies might collapse, and what kinds of dynamics are in play, using the Roman Empire as a case study that we start out from. Or maybe we decide that this isn’t valuable enough in comparison to the other things that we could be teaching, and we decide to throw away the whole topic.
Why do so many children (and adults!) dislike school? Probably because static representations are often bad at teaching dynamic models, and many teachers might not even realize that that’s what they’re supposed to be teaching. This creates the feeling that school learning is boring, unless the student is already talented at turning the static explanations into dynamic models. Which isn’t to say that writing is all bad: it’s much easier and faster to create, and if the learner can connect the writing to content that’s already in the learner’s head, it can be a very effective way of deepening and broadening one’s understanding. When you already know have a good model of the domain in question, even static materials can be easy to translate into dynamic components that you can add to and integrate with your existing model. The problem only occurs when there isn’t anything that the learner could connect the material to. James Paul Gee compares reading game manuals with reading science texts:
But, in any case, the problem with the texts associated with video game—the instruction booklets, walkthroughs, and strategy guides—is that they do not make a lot of sense unless one has already experienced and lived in the game world for a while. Of course, this lack of lucidity can be made up for if the player has read similar texts before, but at some point these texts originally made sense because the player had an embodied world of experience in terms of which to situate and spell out their meanings.
The same thing is most certainly true of the sorts of texts that show up in learning content areas like science and math in school, especially in the later grades, high school, and college. A biology textbook does not make a lot of sense unless and until one has experienced and lived in the world of biology as practice for a while. And again, this lack of lucidity is mitigated if the student has already read a good many similar texts. However, at some point these texts also originally made sense because the student had an embodied world of experience (in reality or, at least, simulated in his or her mind) in terms of which to situate and spell out their meanings.
When I give talks on video games to teachers, I often show them a manual or strategy guide and ask them how much they understand. Very often they are frustrated. They have no experience in which to situate the words and phrases of the texts. All they get is verbal information, which they understand at some literal level, but which does not really hang together. They cannot visualize this verbal information in any way that makes sense or makes them want to read on. I tell them that that is how their students often feel when confronted with a text or textbook in science or some other academic area if they have had no experiences in terms of which they can situate the meanings of the words and phrases. It’s all “just words,” words the “good” students can repeat on tests and the “bad” ones can’t. — What Video Games Have to Teach Us about Learning and Literacy, pp. 102-103.
To be fair, there are many school teachers who really do focus on teaching a genuine understanding of content, and make a good job of it – the traditional school system isn’t all bad. I had such teachers on all grades, and often they were successful at their pursuits. But they were still required to assign grades, and it is hard to genuinely and fairly test a student’s understanding in some domain if you cannot actually place them in that domain. Ultimately, they too assigned grades based on things like tests and projects, which are fundamentally static measures of understanding and have a hard time measuring dynamic understanding. The need to assign grades, and to measure performance by some fair (and thus, in a pre-computer era, mostly static) method, crucially handicapped efforts aimed at really improving the understanding of the students.
Of course, current edugames aren’t really set up to deliver a new kind of educational experience. Rather, many are designed as aids for teaching the informational content of the existing curriculum – which is rather backwards, when you think of it. We’d really want our students to learn dynamic models but we can’t teach or test those directly, so we teach and test them on static facts instead – and when we finally do get an instructional aid that could teach and test dynamic models, we try to fit it into the mold of teaching facts, because that’s what they’ll be tested on!
It probably isn’t a coincidence that so many edugames are about mathematics, because math is the subject that’s the closest to being tested in a dynamic way, and is thus the most naturally suited for computer instruction.
Another issue that we aren’t yet very good at making games that teach dynamic models. Ian Bogort has coined a term for the teaching of dynamic models: procedural rhetoric. Just as verbal rhetoric is the art of persuading and teaching by using spoken words, while visual rhetoric does the same using pictures, procedural rhetoric persuades and educates by using a dynamic model. Let’s look at his argument in a little more detail.
One way of defining a game is as a collection of rules that define various consequences for the actions that a player takes. Shoot at the alien, the alien loses hit points and gets angry at you. Thus, when somebody plays a game, they are placed in a microcosm where the laws of cause and effect have been defined by the designer of the game, and they need to learn and internalize those laws in order to succeed at the game. In effect, the game designer can be seen as making a statement about the kinds of causal laws that exist, and the player comes to understand that position via their own experience, having discovered and experienced the laws for themselves.
Now the causal laws of many video games are mostly only applicable within the video game itself, and few people think of applying them in any other context. But games could present broader arguments. One of Bogort’s examples is The McDonald’s Videogame, in which
The player controls four separate aspects of the McDonald’s production environment, each of which he has to manage simultaneously: the third-world pasture where cattle are raised as cheaply as possible; the slaughterhouse where cattle are fattened for slaughter; the restaurant where burgers are sold; and the corporate offices where lobbying, public relations, and marketing are managed. In each sector, the player must make difficult business choices, but more importantly he must make difficult moral choices. In the pasture, the player must create enough cattle-grazing land and soy crops to produce the meat required to run the business. But only a limited number of fields are available; to acquire more land, the player must bribe the local governor for rights to convert his people’s crops into corporate ones. More extreme tactics are also available: the player can bulldoze rainforest or dismantle indigenous settlements to clear space for grazing (see figure 1.1). — Ian Bogort, Persuasive Games: The Expressive Power of Videogames, Kindle Locations 721-728.
Presumably, the game designers hope that by playing the game, the player comes to see the laws of cause and effect that push corporations towards unethical behavior by sometimes making it more profitable than ethical behavior. Having personally experienced a situation where those laws operated, the player can apply their experience more generally, and start to be more suspicious about the behavior of not only McDonald’s, but any corporation which is operating under similar laws of cause and effect. Of course, the player may reject the argument and feel that the position that the game designers are advocating is a flawed one – but that is the case with all rhetoric.
The ultimate goal of procedural rhetoric in the service of education is to give the player a genuine understanding of the laws operating in a game, in a way that allows for that understanding to be generalized to similar situations in real life, while also being fun. That’s a very tough challenge, and we don’t really know how to do it yet. On the other hand, there are already games that can be used for a similar purpose despite not being explicitly educational, such as by having students try to evolve a humanity-eradicating plague in Plague Inc. and then talking about the lessons about evolution that this teaches [1 2]. Such an approach is probably the most effective one for now, but it could be much improved if we had games designed expressly for the task.
If we did, we could truly revolutionize schooling. Throw away exams and grades, and just give kids games to play with, and have discussions about the games afterwards. If we wanted to have some measure of how far the students had progressed, just look at how much they had achieved in the game. Of course, massive changes of this kind are going to face a lot of resistance, so for now edugame designers who agree with these goals should be working towards more gradually shifting the system in this direction.
Another important skill, which both Gee and Bogort emphasize, is the ability to study models critically. It’s not enough that we teach students different models of how the world works – they also need to learn to evaluate the merits and plausibility of different models. What simplifying assumptions are being made? How does this model mesh together with others? How can one validate the claims made by a model? And so on.
Some of this can be taught by simple means, such as having the students play a model and then ask them to look for differences between it and reality. But there’s also a certain beauty in the discovery that the process by which models are created, evaluated, and argued for is itself a process, and can thus be modeled as a game whose laws and caveats can be learned by playing it. My Bayesian Academy game is one attempt to teach critical evaluation of models by showing some of the ways by which information can be unreliable.
And then, of course, the students will be asked to critically evaluate the model about critically evaluating models. Maybe we’ll even have a game about that.